3688

Physically-Based Interactive Flow Visualization Based on Schlieren and Interferometry Experimental Techniques

Carson Brownlee, Vincent Pegoraro, Siddharth Shankar, Patrick S. McCormick, Charles D. Hansen
University of Utah, Salt Lake City
IEEE Transactions on Visualization and Computer Graphics, 2010

@article{brownleephysically,

   title={Physically-Based Interactive Flow Visualization Based on Schlieren and Interferometry Experimental Techniques},

   author={Brownlee, C. and Pegoraro, V. and Shankar, S. and McCormick, P. and Hansen, C.},

   journal={Visualization and Computer Graphics, IEEE Transactions on},

   number={99},

   pages={1–1},

   issn={1077-2626},

   publisher={IEEE},

   year={2010}

}

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Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph, interferometry and schlieren imaging for centuries which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. Interferometry tracks changes in phase-shift resulting in bands appearing. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraph, schlieren and interferometry images of time-varying scalar fields derived from computational fluid dynamics (CFD) data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Applications of our method to multi-field data and custom application-dependent color filter creation are explored. Results comparing this method to previous schlieren approximations are finally presented.
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